{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://pptwinpics.oss-cn-beijing.aliyuncs.com/%E7%BB%8F%E7%AE%A1%E4%B9%8B%E5%AE%B6%E9%95%BF%E6%9D%A1%E5%9B%BE_20200321134028.png)\n",
    "\n",
    "大家好，我是 CDA 曹鑫。\n",
    "\n",
    "我的 Github 地址：https://github.com/imcda 。\n",
    "\n",
    "我的邮箱：caoxin@cda.cn 。\n",
    "\n",
    "这节课跟大家讲讲 Matplotlib。\n",
    "\n",
    "# 前言\n",
    "\n",
    "Matplotlib Usage Guide\n",
    "\n",
    "# 参考\n",
    "\n",
    "链接：https://matplotlib.org/tutorials/introductory/usage.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sphinx_gallery_thumbnail_number = 3\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "fig = plt.figure()  # an empty figure with no axes\n",
    "# fig.suptitle('No axes on this figure')  # Add a title so we know which it is\n",
    "\n",
    "# fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.43109431 0.81561877 0.74336452 0.2701683  0.21707693]\n",
      " [0.63025951 0.67703487 0.91178016 0.99123691 0.06724475]\n",
      " [0.10796955 0.832646   0.34523839 0.26510611 0.85904519]\n",
      " [0.43171967 0.34031579 0.11254958 0.04399059 0.64204754]]\n"
     ]
    }
   ],
   "source": [
    "a = pd.DataFrame(np.random.rand(4,5), columns = list('abcde'))\n",
    "a_asarray = a.values\n",
    "print(a_asarray)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]]\n"
     ]
    }
   ],
   "source": [
    "b = np.matrix([[1,2],[3,4]])\n",
    "b_asarray = np.asarray(b)\n",
    "print(b_asarray)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 2, 100)\n",
    "\n",
    "plt.plot(x, x, label='linear')\n",
    "plt.plot(x, x**2, label='quadratic')\n",
    "plt.plot(x, x**3, label='cubic')\n",
    "\n",
    "plt.xlabel('x label')\n",
    "plt.ylabel('y label')\n",
    "\n",
    "plt.title(\"Simple Plot\")\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.  0.2 0.4 0.6 0.8 1.  1.2 1.4 1.6 1.8 2.  2.2 2.4 2.6 2.8 3.  3.2 3.4\n",
      " 3.6 3.8 4.  4.2 4.4 4.6 4.8 5.  5.2 5.4 5.6 5.8 6.  6.2 6.4 6.6 6.8 7.\n",
      " 7.2 7.4 7.6 7.8 8.  8.2 8.4 8.6 8.8 9.  9.2 9.4 9.6 9.8]\n"
     ]
    }
   ],
   "source": [
    "x = np.arange(0, 10, 0.2)\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = np.sin(x)\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
